Effect of GSTM2-5 Polymorphisms on Lung Function Growth
Effect of GSTM2-5 Polymorphisms on Lung Function Growth
Results suggest that variation within the GSTM3 and GSTM5 loci had significant impact on lung function outcomes at age 18 after adjustment for confounding. Some diplotypes, but none of their interactions with smoke exposure (in utero, SHS, or active smoking exposure at 18), produced an independent, statistically significant relationship with FEV1 and FVC, but not with FEV1/FVC. Additional analyses suggest a multi-stage model. First, DNA methylation was affected by diplotypes conditionally on smoking exposure; second, an altered DNA methylation modified the effect of diplotypes on lung function (acting as modGVs), leading to significant effects of GSTM2 and GSTM5 on FEV1 and FVC. Path analyses show that methylation at cg06970744 did not lie on the pathway between GSTM5 diplotypes and lung function, further providing evidence that methylation at certain sites can modify the effect of genetic variation on an outcome. Also, methylation at this site appears to be unaffected by nearby SNPs (unpublished observations).
Several GSTM3 diplotypes had strong, negative effects on gain in lung function. SNPs in GSTM3 included a functional SNP (rs7483). Previous studies have found an association with this SNP and Alzheimer's disease. Breton et al. have previously examined the association of rs7483 with lung function, and similar to the present study, no significant associations were found.GSTM4 had a synonymous coding SNP (rs506008). This SNP produced positive, but insignificant effects on lung function across time and thus more than likely does not make contributions to lung function at the diplotype level. There are no reported associations between rs506008 and any disease outcomes. Although GSTM5 had no functional SNPs, there was a significant lung function improvement in those who possessed the AA_CA diplotype, demonstrating a need to investigate this particular region. Only one of the SNPs (rs11807) was previously reported in the literature, showing a strong association with hypertension; however, no association with lung function had been reported.
Due to previous findings that showed lower lung function outcomes due to various tobacco smoke exposures, we assessed the critical period where lung development may be severely impaired by tobacco smoke exposure. No two-way interaction effects of tobacco smoke with GSTM2-5 loci were seen, which is in contrast to findings by Breton et al., who reported interaction effects with GSTM2 and in utero tobacco smoke. This discrepancy may be either due to misclassification of the exposure and/or insufficient sample size in our study or missing replication in the study by Breton et al.. Because questions involving tobacco smoke exposure at age 18 were validated with urinary cotinine levels (Additional file 3: Table S9), there is no suggestion of major misclassification, as those who were active smokers or were exposed to SHS had significantly higher levels of cotinine compared to nonsmokers. The study by Breton et al. included at least one more repeated measurement, hence, it is possible that the present study does not have equal statistical power to detect interactions. However, there is a need of replication studies to examine the role of these genes on lung function in conjunction with tobacco smoke exposure, especially in different environments. It is also necessary to consider that other environmental and lifestyle exposures including air pollution and paracetamol (acetaminophen) use may also alter oxidative stress and mask or falsely indicate an effect of related exposures. Air pollution was not controlled in the study by Breton et al., but was reported to modify the effect of a similarly functioning gene (GSS) on lung function growth in another study of this group. Because it has been suggested in the literature that tobacco smoke exposure, especially in utero, may epigenetically modify these genes, hence changing the function of these genes, we tested the effect of CpG sites on lung function levels at age 18. Although there were no independent effects of these CpG site methylation levels on lung function outcomes, it is interesting to note that these effects were not seen until joint effects of GSTM2 and GSTM5 diplotypes were taken into account, indicating that DNA methylation may modify the effect of genetic variants on lung function, a mechanism that needs further investigation. These findings may also help explain the lack of consistency between the present study's findings and the findings of Breton et al.. It may not be the genotype that produces inconsistent results, but rather different DNA methylation levels in different study groups that accounted for the discrepancy.
To further lend validity to this study, selection bias was not apparent regarding availability of lung function data. Approximately 95% (1456/1536) of mother-child pairs were enrolled into this study; and those who underwent pulmonary function tests were not significantly different from the total cohort (Table 1). Also, lung function measurements were obtained under standardized conditions in a prospective manner, decreasing the likelihood of information bias. With respect to genotyping data, all SNPs that were shared with Breton et al. were in HWE and had comparable frequencies with Caucasians in their sample. These polymorphisms also agreed substantially in their association with FEV1 and FVC with our findings (Additional file 1: Figure S2 and Additional file 2: Figure S3). In regard to haplotypes, diplotypes (haplotype-pairs) were used, thus reducing uncertainty and subsequently misclassification of individuals, which is often encountered in haplotype association studies. Also, our population was homogeneous, meaning controlling for population stratification is unnecessary and ensures HWE, which appeared to be an issue for Breton et al., possibly resulting in different findings. While SNPs included in the haplotype analysis of the latter study were in HWE within ethnic groups, they were not in HWE when examining the entire population. This is problematic because inclusion of SNPs that deviate from HWE may produce spurious associations between haplotypes and lung function. In addition, the findings by Breton et al. may be due to population stratification. The authors identified ancestry indicators, controlled these as confounders but did not stratify their analysis by these markers. Nevertheless, population stratification addresses the possibility that haplotypes may reveal different associations in different ethnic/racial strata. This may also account for the lack of agreement of single SNP effects on lung function outcomes between the present study and the Breton et al. study.
Despite the strengths of our study, some limitations are present. First, because maternal smoking and active smoking during adolescence is obtained via self-reported questionnaires, misclassification of this exposure is possible. Our previous publications have shown that maternal smoking during pregnancy interacts with the IL13 and IL1RN genes and increases the risk of asthma and wheezing. Hence, ascertainment of maternal smoking seemed to provide valid information. However, maternal smoking × IL13 and IL1RN gene interaction assumes an effect of smoking on these genes. Against that, GSTM2-5 × maternal smoking interactions assume that the genes regulate the toxicity of tobacco smoke, possibly via epigenetic mechanisms. Also, based on results of the methylation analyses in the present study, the joint effect of maternal smoking and GSTM2-5 diplotypes did not influence methylation levels of CpG sites within the GSTM2-5 cluster; however, these methylation levels were captured at age 18 and therefore we cannot ascertain whether or not epigenetic changes had taken place due to this particular exposure nor can we determine that methylation levels at age 18 are representative of early-life methylation profiles. Regarding validation of other smoke exposures, passive smoke exposure and active smoking at age 18 was associated with increased cotinine levels. Also, active smoking at age 18 led to deficits in FEV1/FVC after adjustments for GSTM5 diplotype, GSTM1 genotype, sex, BMI, height, in utero smoke exposure, and SHS (Additional file 3: Table S16). Reduced FEV1/FVC has previously been observed in adolescent smokers.
Second, not all SNPs used in the Breton et al. study were genotyped in this work. Therefore combinations of SNPs that were not included in the haplotype construction may lead to different results. Variation in FEV1 in these results may be due to differences in population characteristics between the two studies, residual confounding, or as demonstrated by methylation levels, differences in expression levels of detoxification enzymes produced by this set of genes. Based on the results of this study, methylation levels at age 18 within this gene cluster can be ruled out because analyses revealed no significant effect of methylation on lung function levels at 18. The goal of this study was to expand upon findings by Breton et al. through accounting for methylation.
Discussion
Results suggest that variation within the GSTM3 and GSTM5 loci had significant impact on lung function outcomes at age 18 after adjustment for confounding. Some diplotypes, but none of their interactions with smoke exposure (in utero, SHS, or active smoking exposure at 18), produced an independent, statistically significant relationship with FEV1 and FVC, but not with FEV1/FVC. Additional analyses suggest a multi-stage model. First, DNA methylation was affected by diplotypes conditionally on smoking exposure; second, an altered DNA methylation modified the effect of diplotypes on lung function (acting as modGVs), leading to significant effects of GSTM2 and GSTM5 on FEV1 and FVC. Path analyses show that methylation at cg06970744 did not lie on the pathway between GSTM5 diplotypes and lung function, further providing evidence that methylation at certain sites can modify the effect of genetic variation on an outcome. Also, methylation at this site appears to be unaffected by nearby SNPs (unpublished observations).
Several GSTM3 diplotypes had strong, negative effects on gain in lung function. SNPs in GSTM3 included a functional SNP (rs7483). Previous studies have found an association with this SNP and Alzheimer's disease. Breton et al. have previously examined the association of rs7483 with lung function, and similar to the present study, no significant associations were found.GSTM4 had a synonymous coding SNP (rs506008). This SNP produced positive, but insignificant effects on lung function across time and thus more than likely does not make contributions to lung function at the diplotype level. There are no reported associations between rs506008 and any disease outcomes. Although GSTM5 had no functional SNPs, there was a significant lung function improvement in those who possessed the AA_CA diplotype, demonstrating a need to investigate this particular region. Only one of the SNPs (rs11807) was previously reported in the literature, showing a strong association with hypertension; however, no association with lung function had been reported.
Due to previous findings that showed lower lung function outcomes due to various tobacco smoke exposures, we assessed the critical period where lung development may be severely impaired by tobacco smoke exposure. No two-way interaction effects of tobacco smoke with GSTM2-5 loci were seen, which is in contrast to findings by Breton et al., who reported interaction effects with GSTM2 and in utero tobacco smoke. This discrepancy may be either due to misclassification of the exposure and/or insufficient sample size in our study or missing replication in the study by Breton et al.. Because questions involving tobacco smoke exposure at age 18 were validated with urinary cotinine levels (Additional file 3: Table S9), there is no suggestion of major misclassification, as those who were active smokers or were exposed to SHS had significantly higher levels of cotinine compared to nonsmokers. The study by Breton et al. included at least one more repeated measurement, hence, it is possible that the present study does not have equal statistical power to detect interactions. However, there is a need of replication studies to examine the role of these genes on lung function in conjunction with tobacco smoke exposure, especially in different environments. It is also necessary to consider that other environmental and lifestyle exposures including air pollution and paracetamol (acetaminophen) use may also alter oxidative stress and mask or falsely indicate an effect of related exposures. Air pollution was not controlled in the study by Breton et al., but was reported to modify the effect of a similarly functioning gene (GSS) on lung function growth in another study of this group. Because it has been suggested in the literature that tobacco smoke exposure, especially in utero, may epigenetically modify these genes, hence changing the function of these genes, we tested the effect of CpG sites on lung function levels at age 18. Although there were no independent effects of these CpG site methylation levels on lung function outcomes, it is interesting to note that these effects were not seen until joint effects of GSTM2 and GSTM5 diplotypes were taken into account, indicating that DNA methylation may modify the effect of genetic variants on lung function, a mechanism that needs further investigation. These findings may also help explain the lack of consistency between the present study's findings and the findings of Breton et al.. It may not be the genotype that produces inconsistent results, but rather different DNA methylation levels in different study groups that accounted for the discrepancy.
To further lend validity to this study, selection bias was not apparent regarding availability of lung function data. Approximately 95% (1456/1536) of mother-child pairs were enrolled into this study; and those who underwent pulmonary function tests were not significantly different from the total cohort (Table 1). Also, lung function measurements were obtained under standardized conditions in a prospective manner, decreasing the likelihood of information bias. With respect to genotyping data, all SNPs that were shared with Breton et al. were in HWE and had comparable frequencies with Caucasians in their sample. These polymorphisms also agreed substantially in their association with FEV1 and FVC with our findings (Additional file 1: Figure S2 and Additional file 2: Figure S3). In regard to haplotypes, diplotypes (haplotype-pairs) were used, thus reducing uncertainty and subsequently misclassification of individuals, which is often encountered in haplotype association studies. Also, our population was homogeneous, meaning controlling for population stratification is unnecessary and ensures HWE, which appeared to be an issue for Breton et al., possibly resulting in different findings. While SNPs included in the haplotype analysis of the latter study were in HWE within ethnic groups, they were not in HWE when examining the entire population. This is problematic because inclusion of SNPs that deviate from HWE may produce spurious associations between haplotypes and lung function. In addition, the findings by Breton et al. may be due to population stratification. The authors identified ancestry indicators, controlled these as confounders but did not stratify their analysis by these markers. Nevertheless, population stratification addresses the possibility that haplotypes may reveal different associations in different ethnic/racial strata. This may also account for the lack of agreement of single SNP effects on lung function outcomes between the present study and the Breton et al. study.
Despite the strengths of our study, some limitations are present. First, because maternal smoking and active smoking during adolescence is obtained via self-reported questionnaires, misclassification of this exposure is possible. Our previous publications have shown that maternal smoking during pregnancy interacts with the IL13 and IL1RN genes and increases the risk of asthma and wheezing. Hence, ascertainment of maternal smoking seemed to provide valid information. However, maternal smoking × IL13 and IL1RN gene interaction assumes an effect of smoking on these genes. Against that, GSTM2-5 × maternal smoking interactions assume that the genes regulate the toxicity of tobacco smoke, possibly via epigenetic mechanisms. Also, based on results of the methylation analyses in the present study, the joint effect of maternal smoking and GSTM2-5 diplotypes did not influence methylation levels of CpG sites within the GSTM2-5 cluster; however, these methylation levels were captured at age 18 and therefore we cannot ascertain whether or not epigenetic changes had taken place due to this particular exposure nor can we determine that methylation levels at age 18 are representative of early-life methylation profiles. Regarding validation of other smoke exposures, passive smoke exposure and active smoking at age 18 was associated with increased cotinine levels. Also, active smoking at age 18 led to deficits in FEV1/FVC after adjustments for GSTM5 diplotype, GSTM1 genotype, sex, BMI, height, in utero smoke exposure, and SHS (Additional file 3: Table S16). Reduced FEV1/FVC has previously been observed in adolescent smokers.
Second, not all SNPs used in the Breton et al. study were genotyped in this work. Therefore combinations of SNPs that were not included in the haplotype construction may lead to different results. Variation in FEV1 in these results may be due to differences in population characteristics between the two studies, residual confounding, or as demonstrated by methylation levels, differences in expression levels of detoxification enzymes produced by this set of genes. Based on the results of this study, methylation levels at age 18 within this gene cluster can be ruled out because analyses revealed no significant effect of methylation on lung function levels at 18. The goal of this study was to expand upon findings by Breton et al. through accounting for methylation.
Source...